筛选结果
10 篇排序
1:29:02EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2026年7月1日播客从每天 50 个设计到 1500 个：AI 如何改变了捷豹路虎的探索范围主持 Nathan LabenzNeural Concept 的 Thomas von Tschammer 谈专业物理模型、工程副驾（engineering copilot），以及为什么一级方程式赛车（Formula 1）已经能在一夜之间跑完上千种设计。
1:50:08EN → 简体中文Cognitive Revolution "How AI Changes Everything"· 2024年8月7日播客Waymo 的受伤率低了五倍，却仍输给一辆 Lyft主持 Nathan Labenz人类司机平均每 1 亿英里才发生一起致命事故，这道门槛至今仍是自动驾驶争论的标尺。
1:16:11EN → 简体中文Cognitive Revolution "How AI Changes Everything"· 2024年7月11日播客把食物舀进餐盒，占了工厂人工的 70%主持 Nathan LabenzChef Robotics 首席执行官 Rajat Bhageria 谈 2000 万份装盘餐食、食品领域的基础模型，以及厨房为什么可能搬出住宅。
1:20:44EN → 简体中文Cognitive Revolution "How AI Changes Everything"· 2024年3月30日播客像 Mamba 一样看世界：视觉、腐坏的状态与 90 天里的细胞模型主持 Nathan LabenzNathan Labenz 和 Jason Meaux 梳理了原版 Mamba 发布之后的视觉论文、长上下文实验和生物学工作。
1:40:07EN → 简体中文Cognitive Revolution "How AI Changes Everything"· 2023年7月4日播客每秒 30,000 次电压更新：深入 Skydio 的自主技术栈主持 Nathan LabenzHayk Martiros 带 Nathan Labenz 逐一了解一架约 0.9 公斤重的无人机：它能看向四面八方，机上运行十多个神经网络，而且不会被武器化。
1:25:16EN
Lex Fridman播客From Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional Networks主持 Lex FridmanA 2016 Deep Learning School talk covering how convnets work, how the ImageNet winners evolved, and how to apply them without being a hero.
1:11:50ENLex Fridman播客Data Is Everything: Teaching Self-Driving Cars to Understand the Human Behind the Wheel主持 Lex FridmanIn an MIT lecture, Lex Fridman shows how deep learning can sense pedestrians, driver posture, gaze, emotion and cognitive load, and why that matters for human-centered autonomy.
1:19:52ENLex Fridman播客From Pixels to Steering Wheels: Convolutional Networks and End-to-End Driving主持 Lex FridmanLex Fridman's MIT 6.S094 lecture explains how convolutional neural networks work, where deep learning helps a self-driving car, and how to train a network to steer from video.
1:13:22ENLex Fridman播客The Second 90%: What It Really Takes to Put Deep Learning on a Driverless Car主持 Lex FridmanWaymo's Sacha Arnoud walks MIT students through Waymo's history, its perception stack, and the industrial-scale labeling, compute and testing behind it.
53:13ENLex Fridman播客How Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene Segmentation主持 Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the basics of image classification through landmark network architectures to pixel-level segmentation, optical flow and the SegFuse competition.